In contrast to the datasets described above, the size of the datasets we are feeding to our, data-hungry, deep learning models in many other areas of research is simply not comparable. For instance, the number of 3D assets used in training generative 3D models is, maximally, on the order of thousands [1]} and the simulators used to train embodied AI models typically have only between a few dozen to a thousand unique scenes [2]}, [3]}, [4]}, [5]}. The startling advances brought about by developing large-scale datasets for images, videos, and natural language, demand that an equivalent dataset be built for 3D assets.
